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Paroma, aptly nicked ‘Alice in Wordland’ by her peers for her enthusiasm to explore the world of words, crafts compelling features around the fast-growing marketing technology space. As General Assignments Editor, she focuses on the vision of the key players in this industry even while highlighting the interesting side stories around martech companies. With over a decade of dabbling with various forms of writing and working closely with award-winning advertising agencies to launch premium brands in the Travel, Luxury and Real Estate space, she’s now keen to explore all the technology that helps put all this CX interface into place. A music and dance aficionado, Mademoiselle Paroma is as conversant with French as she is with numbers thanks to her five-year stint as an investment banker. She counts ‘Gone with the Wind’ as her fave rainy-day-cuppa-coffee read and ‘Into the Wild’ as the movie she can cozy up on her couch with.

Share your insights into martech happenings with Paroma on paroma.sen@martechadvisor.com

A 2017 Pegasystems study shared how 64% of companies say they know their customers well.
Great! But wait. Here’s the climax.

Only 24% of customers feel the same way.

There are constant discussions about the changing habits of consumers largely influenced by the influx of improved digital options and technology progresses. And it’s true that the consumer of today has certain wants that even B2B marketers now have to open up to.

This is the engagement economy. Irrespective of whether you are a B2B marketer or a B2C marketer - if you are unable to engage with customers meaningfully, you will lose out.

There is a gap in deeply knowing customers. Without embedding strategic plans to create a strong customer connect with each marketing effort, businesses cannot go from being vendors to trusted and strategic growth partners. A strong customer connect is important to be able to co-create value for a fruitful long-term relationship. No business can survive without knowing their customer.

The great part is, there are 3 interesting technologies that can give your business a sizeable edge by helping you understand your consumer a lot better.

Ultimately, in this engagement and experience economy it’s all about creating value for the customer and with the customer.

According to Salesforce’s 2016 Connected Customer report, by 2020, 57% of business buyers will depend on companies to anticipate their needs and if they don’t, business buyers will have no problem switching brands.

So then, maybe it’s time to UP the customer connect game.

These 3 technologies - Machine learning, Big Data and Cloud Computing - though ostensibly serving other needs, also play a great role in helping B2B marketers get closer to customers.

This is how.

Machine learningUsing machine learning algorithms, businesses can better optimize and discover statistical patterns in their customer’s buying behavior and this forms the backbone of predictive analytics. The rich insights collected can help marketers know what direction their customers are headed besides also anticipating future buying patterns. Machine learning can also help identify and acquire prospects with attributes similar to existing customers thereby cutting down lead identification time cycles for marketers.

1. Machine learning augments the lead generation the entire process: Innumerable hours of manpower can go into the entire lead generation cycle. Every part of the process requires stringent follow-up, planning and execution for every task, from sourcing new leads to finding the right contact information. Machine learning powered technology can not only help with the process of gathering the most relevant lead data and enrich the data but determine the patterns and intent that helps marketers move faster and focus on the right prospect at the right time.

Here’s where the value-add lies. How it brings a deeper connect between the business and customer is not just because it reduces operational timelines. The unstructured data that is eventually broken down by technology differentiates the best-fit leads from others that are less likely to purchase or even express interest in your product in future.This crucial data can further help you power more personalized, seamless and omni-channel marketing campaigns to create a better customer connect much in line with the current consumer trends and demands of today. And your efforts could be focused on only those best-fit leads.

Josh Ong, Director of Global Marketing and Communications, Cheetah Mobile comments, “Machine Learning at the right stage of the process does some of the analytical work for us by augmenting dashboards that require human insight. Machines are able to identify patterns to optimize our platforms, which is where you really start to scale and see the power of the analytics.”

2. Predictive features for enhanced Lead Management that also compliments ABM efforts: Data is big. For every business. When predictive analytics is applied to your prospecting efforts it can help prioritize where and how you should focus the majority of your sales efforts. In a time where Account-based marketing is fast becoming the name of the game, machine learning abilities help boost ABM efforts. Account-based Marketing at its core is an endeavor where marketers identify their targeted Accounts (and their needs) and then gainfully transition them through the stages of the buying journey with highly personalized content. Strategizing campaigns for these set of accounts using predictive behavior and analytics will support the aim of delivering a more seamless experience. On the whole this serves to bring your brand much closer to the customer.

Josh adds, “An analytics dashboard can provide a wealth of data for a company and is essentially the combination of Big Data and the Cloud. Analytics is the start to gleaning meaningful insight from the data around us everyday.”

In B2B and B2C marketing, using predictive analytics to enhance efforts are already becoming commonplace. To experience this, all one has to do is spend some time on any social media platform to see what ads are in their feed. While we are used to customized ads based on our previous ‘likes’, today the machine learning powered recommendation engines tell us proactively what we may be interested in too.

B2B marketers also (already) use predictive behavior to offer customers suggestions and ideas about what services or products would complement their business and existing solutions in much the same way. Customers do start then believing that their vendor knows their business.

Amazon mastered the art of recommending products across various categories that their customers might be interested in. Other companies do it other ways, such as recommending music on Spotify, movies on Netflix, or Pins on Pinterest.

3. Improving cold calling efforts: Phone and emails are still a strong part of sales and marketing. But here, when it comes to cold calls, tracking, analyzing and improving them should be the main concern. The problem is, its difficult to do that. Within the realm of machine-learning now falls conversation intelligence. Companies like Marketo have started offering ‘Conversation Intelligence’ solutions.What these can do is record, transcribe, analyze sales calls with the help of NLP (Natural Language Processing). The tool can perform these tasks in real-time and in some cases also highlight the topics of importance that crop up during a call. Some solutions may also flag moments during a call when a customer has a pain point over pricing, mentions a competitor’s name, etc. All of this can be indicators that can give client-facing Sales teams deeper customer insights thereby helping them improve on how they close a deal while also creating a more succinct customer connect. It is the power of machine learning to help process unstructured data- a thus far overlooked goldmine of customer intelligence.

Tasso Argyros, CEO and founder of ActionIQ adds, “With the ever-expanding influx of information available about customers, technology innovation in machine learning, big data and cloud enable marketers to deeply understand what influences and drives customer behaviors so they can deliver products to them at the right place and the right time. Customers constantly have to make decisions about the products they purchase, but marketers can gain a competitive advantage by ensuring they deliver the right information at the right time based on a deep understanding of their customers profile and shopping behaviors due to the advancements in machine learning and cloud-based big data solutions.”

Big DataBig Data can help B2B marketers build a robust 360-degree customer view, and be more responsive to their customer’s needs.

1. Big Data to drive a deeper breakdown of your customer information:Big data, is data gathered by a combination of predictive analytics, user behavior analytics, or certain other advanced data analytics methods that eventually help extract most value from the data. The point is, what is most important is not the data itself but what marketers do with all this data.For any thriving business, Sales and Marketing data can tell you a lot more about your customers. Big data serves as a base to provide insightful analytics because the information has to be curated and organized to be used as insights and results. Marketing is all about reaching the right customer, and data can be used to predict purchases, analyze current and percepted behavior, better understand the people buying the product or showing interest in them or even create a thorough customer persona that includes details on income level, lifestyle, personal goals besides the basics like age and gender. Over and above this, it can also help breakdown the information to know who your best customers are.

Analytics are great but are only as good as the data they are based upon. Sometimes organizational hurdles and technological lags leave many businesses struggling with gathering the most relevant data to feed their analytics. Knowing where and how-to breakdown the data is important to reveal the most interesting and critical behavioral insights. Big data can predict what customers want, leads to improved customer service interactions, quicker understanding of the customer pain points to pursue faster delivery of solutions. Companies today can gather tons of data on their customer. Not only data on purchases but also what websites they visit, where there live, what their last problem was when they contacted customer service. Imagine the endless possibilities you can unlock when you know your customer down to the bone like that.

Jeremy Fain, CEO and co-founder of Cognitiv shares, “Data is the must use feature of AI. Without data, AI, Deep Learning, Machine Learning, or any kind of automated solutions will not bring additional efficiency to an organization. For B2B marketers, this is even more essential, because B2B data levels can be significantly less than for consumer marketers. Every email, every ad shown, every phone call, every lost subscriber, every lead generated, should be stored and formatted in a way that can later be used to train deep learning products. Without clean, big data, the benefits of AI are limited to a marketer.”

Don Lesem, Vice President and Chief Design Officer at IEEE GlobalSpec adds,"Marketers collect tremendous amounts of data. But data-driven marketing means processing that data to better understand user behavior. I ask myself, “Are we getting the expected behavior we want? Are we using our marketing efforts to drive that at a high level?” At IEEE GlobalSpec, that user behavior helps us come to conclusions about what the content we’re putting out should look like. Should it be educational, should it be informative, or entertaining? That then leads to decisions about the content we need to create to move a customer down the funnel. Data is enormously important to the marketing organization. We have such a broad audience; we must focus resources where we’re seeing our campaigns making an impact, and then amplify that. From there, we can use this data to drive other lines of our business, like editorial as an example, so they know what terms are trending, what markets are responding to, and better inform the content being produced. Data also supports our sales teams. We need to look at the difference between marketing qualified leads and cold leads, as each requires a different approach to bring prospective customers to the next stage. We’re able to do that through the data we receive."

Cloud computingSaaS and ‘X-as a service’ models (Iaas, Paas, CPaas and others) have driven greater flexibility and agility in marketing teams. They can now get out of the box solutions made by people who really understand core marketing challenges. Such flexibility and agility lets them not just understand customer better, but to respond faster, make constant tweaks based on the market needs without investing huge sums in technology or committing to long lock-in periods.

1. Cloud for convenience, or marketing clouds for end-to-end solutions: Cloud computing delivers data and services to consumers via the internet. The biggest benefit in using clouds to connect deeper with customers is providing convenience. By using a cloud service program to store your apps, data or product trials, customers won’t need a specific device to access any of it. This is the ideal match for when B2B marketers want to provide a more thorough seamless experience too. Further, when enterprises use cloud facilities for communication, messages and information can be stored on the network as opposed to a particular device. In fact, this is what major communication apps like Skype do. Marketers can use a single cloud platform to manage all their customers. Marketing cloud solutions by companies like Salesforce act as an all in one solution to help a marketer navigate the entire customer journey, including the ability to deliver marketing messages at the right time through the right channel.

With cloud computing, you can tap into your business data to analyze it for patterns, insights, to make predictions, improve forecasting and make other key decisions. Cloud services can provide your organization with higher processing power and sophisticated tools for mining massive amounts of data, as well as the ability to quickly scale your as your data and business grows.

Josh concludes, “Machine Learning, Bid Data and Cloud are a triumvirate that allow brands and B2B companies to intelligently handle scale. The level that most companies are handling customers has exceeded human capacity. Big data is the raw material, Cloud is the storage and computing power we need and Machine Learning is the framework to process and put these large data sets to use. All 3 of these together creates a powerful way for B2B brands to turn any business process into an intelligent one," while Jeremy opines, “Deep Learning, coupled with Big Data - all made possible by the Cloud - can help B2B marketers find new pockets of opportunity and guide sales forces to more efficient resource allocation. The fact is, B2B sales forces spend a very large amount of in long sales cycles with relatively low close rates. Being able to better find the customers more likely to close, spend your time and resources on those, will boost both sales resource ROI and any marketing ROI. Sending the B2B message to people who are similar to those that are already customers is essential to making the most of constrained marketing budgets.”

Tasso says, “The closer B2C marketers can get to their data, without heavy reliance on IT experts or the need for coding, the more they can drive business changing insights from it. These tools must be able to support direct access to data for the business users. Additionally, gaining insights is only half the battle, being able to actually activate these insights is critical - meaning the ability to truly drive action from the insights either directly from the tool or with strong integration into the rest of your martech stack.”

When machines were made to help us identify patterns and process data more efficiently, it only makes good sense to capitalize on these features to further strengthen the bond between a business and its customers, both intended and current.